Visible to the public Biblio

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2022-01-25
Boris, Ryabko, Nadezhda, Savina.  2021.  Development of an information-theoretical method of attribution of literary texts. 2021 XVII International Symposium "Problems of Redundancy in Information and Control Systems" (REDUNDANCY). :70–73.
We propose an information-theoretical method of attribution of literary texts, developed within the framework of information theory and mathematical statistics. Using the proposed method, the following two problems of disputed authorship in Russian and Soviet literature were investigated: i) the problem of false attribution of some novels to Nekrasov and ii) the problem of dubious attribution of two novels to Bulgakov. The research has shown the high efficiency of the data-compression method for attribution of literary texts.
2021-12-20
Griffioen, Paul, Romagnoli, Raffaele, Krogh, Bruce H., Sinopoli, Bruno.  2021.  Resilient Control in the Presence of Man-in-the-Middle Attacks. 2021 American Control Conference (ACC). :4553–4560.
Cyber-physical systems, which are ubiquitous in modern critical infrastructure, oftentimes rely on sending actuation commands and sensor measurements over a network, subjecting this information to potential man-in-the-middle attacks. These attacks can take the form of denial of service attacks or integrity attacks. Previous approaches at ensuring the resiliency of the overall control system against these types of attacks have leveraged functional redundancy in the system, including resilient estimation and reconfigurable control. However, these approaches are only able to ensure resiliency up to a particular subset of the actuator commands and sensor measurements being compromised. In contrast, we introduce a resiliency mechanism in this paper that can ensure safety for the overall system when all the actuator commands and sensor measurements are compromised. In addition, this approach does not require the implementation of any detection algorithm. We leverage communication redundancy in the number of pathways across the network to guarantee safety when up to a certain percentage of those pathways are compromised. The conditions under which safety is guaranteed are presented along with the resiliency mechanism itself, and our results are illustrated via simulation.
2021-11-29
Wang, Yixuan, Li, Yujun, Chen, Xiang, Luo, Yeni.  2020.  Implementing Network Attack Detection with a Novel NSSA Model Based on Knowledge Graphs. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :1727–1732.
With the rapid development of networks, cyberspace security is facing increasingly severe challenges. Traditional alert aggregation process and alert correlation analysis process are susceptible to a large amount of redundancy and false alerts. To tackle the challenge, this paper proposes a network security situational awareness model KG-NSSA (Knowledge-Graph-based NSSA) based on knowledge graphs. This model provides an asset-based network security knowledge graph construction scheme. Based on the network security knowledge graph, a solution is provided for the classic problem in the field of network security situational awareness - network attack scenario discovery. The asset-based network security knowledge graph combines the asset information of the monitored network and fully considers the monitoring of network traffic. The attack scenario discovery according to the KG-NSSA model is to complete attack discovery and attack association through attribute graph mining and similarity calculation, which can effectively reflect specific network attack behaviors and mining attack scenarios. The effectiveness of the proposed method is verified on the MIT DARPA2000 data set. Our work provides a new approach for network security situational awareness.
2021-09-30
Gava, Jonas, Reis, Ricardo, Ost, Luciano.  2020.  RAT: A Lightweight System-Level Soft Error Mitigation Technique. 2020 IFIP/IEEE 28th International Conference on Very Large Scale Integration (VLSI-SOC). :165–170.
To achieve a substantial reliability and safety level, it is imperative to provide electronic computing systems with appropriate mechanisms to tackle soft errors. This paper proposes a low-cost system-level soft error mitigation technique, which allocates the critical application function to a pool of specific general-purpose processor registers. Both the critical function and the register pool are automatically selected by a developed profiling tool. The proposed technique was validated through more than 320K fault injections considering a Linux kernel, different benchmarks and two multicore ARM processors. Results show that our technique significantly reduces the code size and performance overheads while providing reliability improvement, w.r.t. the Triple Modular Redundancy (TMR) technique.
2021-09-16
Lemeshko, Oleksandr, Yeremenko, Oleksandra, Yevdokymenko, Maryna, Ageyev, Dmytro.  2020.  Redundancy Cyber Resiliency Technique Based on Fast ReRouting under Security Metric. 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S T). :815–818.
The paper is devoted to the development and research of the redundancy cyber resiliency technique based on fast rerouting under security metric with the implementation of the basic schemes for network elements protection, namely node, link, path, and bandwidth. Within the model, the secure fast rerouting task is formulated as an optimization problem of nonlinear programming. The model is configured in order to calculate primary and backup paths that contain links with the minimum values of the probability of compromise that is achieved by using the appropriate weights in the objective function, the value of which is minimized. Numerical research has been conducted, results of which proved the proposed model efficiency and adequacy for the practical application.
Venkataramanan, Venkatesh, Hahn, Adam, Srivastava, Anurag.  2020.  CP-SAM: Cyber-Physical Security Assessment Metric for Monitoring Microgrid Resiliency. IEEE Transactions on Smart Grid. 11:1055–1065.
Trustworthy and secure operation of the cyber-power system calls for resilience against malicious and accidental failures. The objective of a resilient system is to withstand and recover operation of the system to supply critical loads despite multiple contingencies in the system. To take timely actions, we need to continuously measure the cyberphysical security of the system. We propose a cyber-physical security assessment metric (CP-SAM) based on quantitative factors affecting resiliency and utilizing concepts from graph theoretic analysis, probabilistic model of availability, attack graph metrics, and vulnerabilities across different layers of the microgrid system. These factors are integrated into a single metric using a multi-criteria decision making (MCDM) technique, Choquet Integral to compute CP-SAM. The developed metric will be valuable for i) monitoring the microgrid resiliency considering a holistic cyber-physical model; and ii) enable better decision-making to select best possible mitigation strategies towards resilient microgrid system. Developed CP-SAM can be extended for active distribution system and has been validated in a real-world power-grid test-bed to monitor the microgrid resiliency.
2021-09-07
Tirupathi, Chittibabu, Hamdaoui, Bechir, Rayes, Ammar.  2020.  HybridCache: AI-Assisted Cloud-RAN Caching with Reduced In-Network Content Redundancy. GLOBECOM 2020 - 2020 IEEE Global Communications Conference. :1–6.
The ever-increasing growth of urban populations coupled with recent mobile data usage trends has led to an unprecedented increase in wireless devices, services and applications, with varying quality of service needs in terms of latency, data rate, and connectivity. To cope with these rising demands and challenges, next-generation wireless networks have resorted to cloud radio access network (Cloud-RAN) technology as a way of reducing latency and network traffic. A concrete example of this is New York City's LinkNYC network infrastructure, which replaces the city's payphones with kiosk-like structures, called Links, to provide fast and free public Wi-Fi access to city users. When enabled with data storage capability, these Links can, for example, play the role of edge cloud devices to allow in-network content caching so that access latency and network traffic are reduced. In this paper, we propose HybridCache, a hybrid proactive and reactive in-network caching scheme that reduces content access latency and network traffic congestion substantially. It does so by first grouping edge cloud devices in clusters to minimize intra-cluster content access latency and then enabling cooperative-proactively and reactively-caching using LSTM-based prediction to minimize in-network content redundancy. Using the LinkNYC network as the backbone infrastructure for evaluation, we show that HybridCache reduces the number of hops that content needs to traverse and increases cache hit rates, thereby reducing both network traffic and content access latency.
2021-08-31
Freitas, Lucas F., Nogueira, Adalberto R., Melgar, Max E. Vizcarra.  2020.  Visual Authentication Scheme Based on Reversible Degradation and QR Code. 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4). :58—63.
Two-Dimensional barcodes are used as data authentication storage tool on several cryptographic architectures. This article describes a novel meaningful image authentication method for data validation using the Meaningless Reversible Degradation concept and QR Codes. The system architecture use the Meaningless Reversible Degradation algorithm, systematic Reed-Solomon error correction codes, meaningful images, and QR Codes. The encoded images are the secret key for visual validation. The proposed work encodes any secret image file up to 3.892 Bytes and is decoded using data stored in a QR Code and a digital file retrieved through a wireless connection on a mobile device. The QR Code carries partially distorted and stream ciphered bits. The QR Code version is defined in conformity with the secret image file size. Once the QR Code data is decoded, the authenticating party retrieves a previous created Reed-Solomon redundancy file to correct the QR Code stored data. Finally, the secret image is decoded for user visual identification. A regular QR Code reader cannot decode any meaningful information when the QR Code is scanned. The presented cryptosystem improves the redundancy download file size up to 50% compared to a plaintext image transmission.
Mahmood, Sabah Robitan, Hatami, Mohammad, Moradi, Parham.  2020.  A Trust-based Recommender System by Integration of Graph Clustering and Ant Colony Optimization. 2020 10th International Conference on Computer and Knowledge Engineering (ICCKE). :598–604.
Recommender systems (RSs) are intelligent systems to help e-commerce users to find their preferred items among millions of available items by considering the profiles of both users and items. These systems need to predict the unknown ratings and then recommend a set of high rated items. Among the others, Collaborative Filtering (CF) is a successful recommendation approach and has been utilized in many real-world systems. CF methods seek to predict missing ratings by considering the preferences of those users who are similar to the target user. A major task in Collaborative Filtering is to identify an accurate set of users and employing them in the rating prediction process. Most of the CF-based methods suffer from the cold-start issue which arising from an insufficient number of ratings in the prediction process. This is due to the fact that users only comment on a few items and thus CF methods faced with a sparse user-item matrix. To tackle this issue, a new collaborative filtering method is proposed that has a trust-aware strategy. The proposed method employs the trust relationships of users as additional information to help the CF tackle the cold-start issue. To this end, the proposed integrated trust relationships in the prediction process by using the Ant Colony Optimization (ACO). The proposed method has four main steps. The aim of the first step is ranking users based on their similarities to the target user. This step uses trust relationships and the available rating values in its process. Then in the second step, graph clustering methods are used to cluster the trust graph to group similar users. In the third step, the users are weighted based on their similarities to the target users. To this end, an ACO process is employed on the users' graph. Finally, those of top users with high similarity to the target user are used in the rating prediction process. The superiority of our method has been shown in the experimental results in comparison with well-known and state-of-the-art methods.
2021-06-30
Wong, Lauren J., Altland, Emily, Detwiler, Joshua, Fermin, Paolo, Kuzin, Julia Mahon, Moeliono, Nathan, Abdalla, Abdelrahman Said, Headley, William C., Michaels, Alan J..  2020.  Resilience Improvements for Space-Based Radio Frequency Machine Learning. 2020 International Symposium on Networks, Computers and Communications (ISNCC). :1—5.
Recent work has quantified the degradations that occur in convolutional neural nets (CNN) deployed in harsh environments like space-based image or radio frequency (RF) processing applications. Such degradations yield a robust correlation and causality between single-event upset (SEU) induced errors in memory weights of on-orbit CNN implementations. However, minimal considerations have been given to how the resilience of CNNs can be improved algorithmically as opposed to via enhanced hardware. This paper focuses on RF-processing CNNs and performs an in-depth analysis of applying software-based error detection and correction mechanisms, which may subsequently be combined with protections of radiation-hardened processor platforms. These techniques are more accessible for low cost smallsat platforms than ruggedized hardware. Additionally, methods for minimizing the memory and computational complexity of the resulting resilience techniques are identified. Combined with periodic scrubbing, the resulting techniques are shown to improve expected lifetimes of CNN-based RF-processing algorithms by several orders of magnitude.
2021-05-25
Barbeau, Michel, Cuppens, Frédéric, Cuppens, Nora, Dagnas, Romain, Garcia-Alfaro, Joaquin.  2020.  Metrics to Enhance the Resilience of Cyber-Physical Systems. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :1167—1172.
We focus on resilience towards covert attacks on Cyber-Physical Systems (CPS). We define the new k-steerability and l-monitorability control-theoretic concepts. k-steerability reflects the ability to act on every individual plant state variable with at least k different groups of functionally diverse input signals. l-monitorability indicates the ability to monitor every individual plant state variable with £ different groups of functionally diverse output signals. A CPS with k-steerability and l-monitorability is said to be (k, l)-resilient. k and l, when both greater than one, provide the capability to mitigate the impact of covert attacks when some signals, but not all, are compromised. We analyze the influence of k and l on the resilience of a system and the ability to recover its state when attacks are perpetrated. We argue that the values of k and l can be augmented by combining redundancy and diversity in hardware and software techniques that apply the moving target paradigm.
2021-05-13
Nie, Guanglai, Zhang, Zheng, Zhao, Yufeng.  2020.  The Executors Scheduling Algorithm for the Web Server Based on the Attack Surface. 2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications( AEECA). :281–287.
In the existing scheduling algorithms of mimicry structure, the random algorithm cannot solve the problem of large vulnerability window in the process of random scheduling. Based on known vulnerabilities, the algorithm with diversity and complexity as scheduling indicators can not only fail to meet the characteristic requirements of mimic's endogenous security for defense, but also cannot analyze the unknown vulnerabilities and measure the continuous differences in time of mimic Executive Entity. In this paper, from the Angle of attack surface is put forward based on mimicry attack the mimic Executive Entity scheduling algorithm, its resources to measure analysis method and mimic security has intrinsic consistency, avoids the random algorithm to vulnerability and modeling using known vulnerabilities targeted, on time at the same time can ensure the diversity of the Executive body, to mimic the attack surface web server scheduling system in continuous time is less, and able to form a continuous differences. Experiments show that the minimum symbiotic resource scheduling algorithm based on time continuity is more secure than the random scheduling algorithm.
2021-05-05
Hallaji, Ehsan, Razavi-Far, Roozbeh, Saif, Mehrdad.  2020.  Detection of Malicious SCADA Communications via Multi-Subspace Feature Selection. 2020 International Joint Conference on Neural Networks (IJCNN). :1—8.
Security maintenance of Supervisory Control and Data Acquisition (SCADA) systems has been a point of interest during recent years. Numerous research works have been dedicated to the design of intrusion detection systems for securing SCADA communications. Nevertheless, these data-driven techniques are usually dependant on the quality of the monitored data. In this work, we propose a novel feature selection approach, called MSFS, to tackle undesirable quality of data caused by feature redundancy. In contrast to most feature selection techniques, the proposed method models each class in a different subspace, where it is optimally discriminated. This has been accomplished by resorting to ensemble learning, which enables the usage of multiple feature sets in the same feature space. The proposed method is then utilized to perform intrusion detection in smaller subspaces, which brings about efficiency and accuracy. Moreover, a comparative study is performed on a number of advanced feature selection algorithms. Furthermore, a dataset obtained from the SCADA system of a gas pipeline is employed to enable a realistic simulation. The results indicate the proposed approach extensively improves the detection performance in terms of classification accuracy and standard deviation.
2021-04-09
Noiprasong, P., Khurat, A..  2020.  An IDS Rule Redundancy Verification. 2020 17th International Joint Conference on Computer Science and Software Engineering (JCSSE). :110—115.
Intrusion Detection System (IDS) is a network security software and hardware widely used to detect anomaly network traffics by comparing the traffics against rules specified beforehand. Snort is one of the most famous open-source IDS system. To write a rule, Snort specifies structure and values in Snort manual. This specification is expressive enough to write in different way with the same meaning. If there are rule redundancy, it could distract performance. We, thus, propose a proof of semantical issues for Snort rule and found four pairs of Snort rule combinations that can cause redundancy. In addition, we create a tool to verify such redundancy between two rules on the public rulesets from Snort community and Emerging threat. As a result of our test, we found several redundancy issues in public rulesets if the user enables commented rules.
2020-11-17
Singh, M., Butakov, S., Jaafar, F..  2018.  Analyzing Overhead from Security and Administrative Functions in Virtual Environment. 2018 International Conference on Platform Technology and Service (PlatCon). :1—6.
The paper provides an analysis of the performance of an administrative component that helps the hypervisor to manage the resources of guest operating systems under fluctuation workload. The additional administrative component provides an extra layer of security to the guest operating systems and system as a whole. In this study, an administrative component was implemented by using Xen-hypervisor based para-virtualization technique and assigned some additional roles and responsibilities that reduce hypervisor workload. The study measured the resource utilizations of an administrative component when excessive input/output load passes passing through the system. Performance was measured in terms of bandwidth and CPU utilisation Based on the analysis of administrative component performance recommendations have been provided with the goal to improve system availability. Recommendations included detection of the performance saturation point that indicates the necessity to start load balancing procedures for the administrative component in the virtualized environment.
2020-10-05
Mitra, Aritra, Abbas, Waseem, Sundaram, Shreyas.  2018.  On the Impact of Trusted Nodes in Resilient Distributed State Estimation of LTI Systems. 2018 IEEE Conference on Decision and Control (CDC). :4547—4552.

We address the problem of distributed state estimation of a linear dynamical process in an attack-prone environment. A network of sensors, some of which can be compromised by adversaries, aim to estimate the state of the process. In this context, we investigate the impact of making a small subset of the nodes immune to attacks, or “trusted”. Given a set of trusted nodes, we identify separate necessary and sufficient conditions for resilient distributed state estimation. We use such conditions to illustrate how even a small trusted set can achieve a desired degree of robustness (where the robustness metric is specific to the problem under consideration) that could otherwise only be achieved via additional measurement and communication-link augmentation. We then establish that, unfortunately, the problem of selecting trusted nodes is NP-hard. Finally, we develop an attack-resilient, provably-correct distributed state estimation algorithm that appropriately leverages the presence of the trusted nodes.

2020-09-28
Gu, Bruce, Wang, Xiaodong, Qu, Youyang, Jin, Jiong, Xiang, Yong, Gao, Longxiang.  2019.  Context-Aware Privacy Preservation in a Hierarchical Fog Computing System. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). :1–6.
Fog computing faces various security and privacy threats. Internet of Things (IoTs) devices have limited computing, storage, and other resources. They are vulnerable to attack by adversaries. Although the existing privacy-preserving solutions in fog computing can be migrated to address some privacy issues, specific privacy challenges still exist because of the unique features of fog computing, such as the decentralized and hierarchical infrastructure, mobility, location and content-aware applications. Unfortunately, privacy-preserving issues and resources in fog computing have not been systematically identified, especially the privacy preservation in multiple fog node communication with end users. In this paper, we propose a dynamic MDP-based privacy-preserving model in zero-sum game to identify the efficiency of the privacy loss and payoff changes to preserve sensitive content in a fog computing environment. First, we develop a new dynamic model with MDP-based comprehensive algorithms. Then, extensive experimental results identify the significance of the proposed model compared with others in more effectively and feasibly solving the discussed issues.
2020-09-18
Kleckler, Michelle, Mohajer, Soheil.  2019.  Secure Determinant Codes: A Class of Secure Exact-Repair Regenerating Codes. 2019 IEEE International Symposium on Information Theory (ISIT). :211—215.
{1 We present a construction for exact-repair regenerating codes with an information-theoretic secrecy guarantee against an eavesdropper with access to the content of (up to) ℓ nodes. The proposed construction works for the entire range of per-node storage and repair bandwidth for any distributed storage system with parameters (n
2020-07-16
Ma, Siyou, Yan, Yunqiang.  2018.  Simulation Testing of Fault-Tolerant CPS Based on Hierarchical Adaptive Policies. 2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C). :443—449.

Cyber physical system (CPS) is often deployed at safety-critical key infrastructures and fields, fault tolerance policies are extensively applied in CPS systems to improve its credibility; the same physical backup of hardware redundancy (SPB) technology is frequently used for its simple and reliable implementation. To resolve challenges faced with in simulation test of SPB-CPS, this paper dynamically determines the test resources matched with the CPS scale by using the adaptive allocation policies, establishes the hierarchical models and inter-layer message transmission mechanism. Meanwhile, the collaborative simulation time sequence push strategy and the node activity test mechanism based on the sliding window are designed in this paper to improve execution efficiency of the simulation test. In order to validate effectiveness of the method proposed in this paper, we successfully built up a fault-tolerant CPS simulation platform. Experiments showed that it can improve the SPB-CPS simulation test efficiency.

2020-04-03
Luo, Xueting, Lu, Yueming.  2019.  A Method of Conflict Detection for Security Policy Based on B+ Tree. 2019 IEEE Fourth International Conference on Data Science in Cyberspace (DSC). :466-472.

Security policy is widely used in network management systems to ensure network security. It is necessary to detect and resolve conflicts in security policies. This paper analyzes the shortcomings of existing security policy conflict detection methods and proposes a B+ tree-based security policy conflict detection method. First, the security policy is dimensioned to make each attribute corresponds to one dimension. Then, a layer of B+ tree index is constructed at each dimension level. Each rule will be uniquely mapped by multiple layers of nested indexes. This method can greatly improve the efficiency of conflict detection. The experimental results show that the method has very stable performance which can effectively prevent conflicts, the type of policy conflict can be detected quickly and accurately.

2020-02-26
Tran, Geoffrey Phi, Walters, John Paul, Crago, Stephen.  2019.  Increased Fault-Tolerance and Real-Time Performance Resiliency for Stream Processing Workloads through Redundancy. 2019 IEEE International Conference on Services Computing (SCC). :51–55.

Data analytics and telemetry have become paramount to monitoring and maintaining quality-of-service in addition to business analytics. Stream processing-a model where a network of operators receives and processes continuously arriving discrete elements-is well-suited for these needs. Current and previous studies and frameworks have focused on continuity of operations and aggregate performance metrics. However, real-time performance and tail latency are also important. Timing errors caused by either performance or failed communication faults also affect real-time performance more drastically than aggregate metrics. In this paper, we introduce redundancy in the stream data to improve the real-time performance and resiliency to timing errors caused by either performance or failed communication faults. We also address limitations in previous solutions using a fine-grained acknowledgment tracking scheme to both increase the effectiveness for resiliency to performance faults and enable effectiveness for failed communication faults. Our results show that fine-grained acknowledgment schemes can improve the tail and mean latencies by approximately 30%. We also show that these schemes can improve resiliency to performance faults compared to existing work. Our improvements result in 47.4% to 92.9% fewer missed deadlines compared to 17.3% to 50.6% for comparable topologies and redundancy levels in the state of the art. Finally, we show that redundancies of 25% to 100% can reduce the number of data elements that miss their deadline constraints by 0.76% to 14.04% for applications with high fan-out and by 7.45% up to 50% for applications with no fan-out.

2020-02-17
Liu, Zhikun, Gui, Canzhi, Ma, Chao.  2019.  Design and Verification of Integrated Ship Monitoring Network with High Reliability and Zero-Time Self-Healing. 2019 Chinese Control And Decision Conference (CCDC). :2348–2351.
The realization principle of zero-time self-healing network communication technology is introduced. According to the characteristics of ship monitoring, an integrated ship monitoring network is designed, which integrates the information of ship monitoring equipment. By setting up a network performance test environment, the information delay of self-healing network switch is tested, and the technical characteristics of "no packet loss" are verified. Zero-time self-healing network communication technology is an innovative technology in the design of ship monitoring network. It will greatly reduce the laying of network cables, reduce the workload of information upgrade and transformation of ships, and has the characteristics of continuous maintenance of the network. It has a wide application prospect.
Khalil, Kasem, Eldash, Omar, Kumar, Ashok, Bayoumi, Magdy.  2019.  Self-Healing Approach for Hardware Neural Network Architecture. 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems (MWSCAS). :622–625.
Neural Network is used in many applications and guarding its performance against faults is a research challenge. Self-healing neural network is a promising concept for achieving reliability, which is the ability to detect and fix a fault in the system automatically. Most of the current self-healing neural network are based on replication of hardware nodes which causes significant area overhead. The proposed self-healing approach results in a modest area overhead and it is suitable for complex neural network. The proposed method is based on a shared operation and a spare node in each layer which compensates for any faulty node in the layer. Each faulty node will be compensated by its neighbor node, and the neighbor node performs the faulty node as well as its own operations sequentially. In the case the neighbor is faulty, the spare node will compensate for it. The proposed method is implemented using VHDL and the simulation results are obtained using Altira 10 GX FPGA for a different number of nodes. The area overhead is very small for a complex network. The reliability of the proposed method is studied and compared with the traditional neural network.
2020-01-20
Krasnobaev, Victor, Kuznetsov, Alexandr, Babenko, Vitalina, Denysenko, Mykola, Zub, Mihael, Hryhorenko, Vlada.  2019.  The Method of Raising Numbers, Represented in the System of Residual Classes to an Arbitrary Power of a Natural Number. 2019 IEEE 2nd Ukraine Conference on Electrical and Computer Engineering (UKRCON). :1133–1138.

Methods for implementing integer arithmetic operations of addition, subtraction, and multiplication in the system of residual classes are considered. It is shown that their practical use in computer systems can significantly improve the performance of the implementation of arithmetic operations. A new method has been developed for raising numbers represented in the system of residual classes to an arbitrary power of a natural number, both in positive and in negative number ranges. An example of the implementation of the proposed method for the construction of numbers represented in the system of residual classes for the value of degree k = 2 is given.

2019-05-01
Hadj, M. A. El, Erradi, M., Khoumsi, A., Benkaouz, Y..  2018.  Validation and Correction of Large Security Policies: A Clustering and Access Log Based Approach. 2018 IEEE International Conference on Big Data (Big Data). :5330-5332.

In big data environments with big number of users and high volume of data, we need to manage the corresponding huge number of security policies. Due to the distributed management of these policies, they may contain several anomalies, such as conflicts and redundancies, which may lead to both safety and availability problems. The distributed systems guided by such security policies produce a huge number of access logs. Due to potential security breaches, the access logs may show the presence of non-allowed accesses. This may also be a consequence of conflicting rules in the security policies. In this paper, we present an ongoing work on developing an environment for verifying and correcting security policies. To make the approach efficient, an access log is used as input to determine suspicious parts of the policy that should be considered. The approach is also made efficient by clustering the policy and the access log and considering separately the obtained clusters. The clustering technique and the use of access log significantly reduces the complexity of the suggested approach, making it scalable for large amounts of data.